A wide range of software tools are available to assist researchers with the process of qualitative data analysis. These include tools that emphasise manual handling of data, (e.g. NVivo, Atlas.ti) and tools that provide some automated analysis based on statistical properties of texts (e.g. Leximancer). These tools are enhancing research, making research activities less complex and tedious, and rendering the process more transparent and portable (Dohan et al. 1998; Welsh 2002; Andrew et al. 2007; Jones 2007). The use of these tools in published works over the last five to ten years has become increasingly more evident. However, in many cases, this increase in frequency of use is also masking the actual method of research. Many researchers who use terms like “Data were analysed using NVivo” are using their chosen analytical package as a proxy for actual embedded methods of analysis. It is possible therefore that Computer-Assisted Qualitative Data Analysis (CAQDA) tools are becoming a substitute for actual, and perhaps valid, techniques for research, analysis and discovery. This paper investigates the extent of this problem, examining CAQDA based papers which have been published over the last five years and reporting on their use, or misuse, of methodology. Further, this paper proposes a solution to the problem by adopting a CAQDA technique which utilises a generic style of methodology. A tool used by Quantitative researchers, known as ‘R’, is available which is a free, open source statistical programming language. Within the last five years R has become the lingua franca for statisticians and applied workers to publish reference implementations for novel quantitative techniques. No such tool with sufficient flexibility exists for qualitative researchers. We describe the initial development of a transparent file format and research process which keeps the researcher close to the data and provides strong safeguards against accidental data alteration. This has two main effects. The transparency of the file format keeps the researcher close to the data, and ensures that the researcher keeps in mind the process used to analyse the data rather than the tool in use. The second effect, also related to the open source, transparent plain text basis of the tool, means that an environment for fostering innovation in qualitative data analysis can be easily provided and freely distributed among workers in the field.